5 papers · 1 filter
Task-Oriented Pre-Training for Drivable Area Detection
Fulong Ma, Guoyang Zhao, Weiqing Qi +2
Pre-training techniques play a crucial role in deep learning, enhancing models' performance across a variety of tasks. By initially training on large datasets and subsequently fine…
Annotation-Free Curb Detection Leveraging Altitude Difference Image
Fulong Ma, Peng Hou, Yuxuan Liu +3
Road curbs are considered as one of the crucial and ubiquitous traffic features, which are essential for ensuring the safety of autonomous vehicles. Current methods for detecting c…
Erase, then Redraw: A Novel Data Augmentation Approach for Free Space Detection Using Diffusion Model
Fulong Ma, Weiqing Qi, Guoyang Zhao +2
Data augmentation is one of the most common tools in deep learning, underpinning many recent advances including tasks such as classification, detection, and semantic segmentation.…
TSCLIP: Robust CLIP Fine-Tuning for Worldwide Cross-Regional Traffic Sign Recognition
Guoyang Zhao, Fulong Ma, Weiqing Qi +4
Traffic sign is a critical map feature for navigation and traffic control. Nevertheless, current methods for traffic sign recognition rely on traditional deep learning models, whic…
FisheyeDepth: A Real Scale Self-Supervised Depth Estimation Model for Fisheye Camera
Guoyang Zhao, Yuxuan Liu, Weiqing Qi +3
Accurate depth estimation is crucial for 3D scene comprehension in robotics and autonomous vehicles. Fisheye cameras, known for their wide field of view, have inherent geometric be…